Surbhi Bhatia
Papers
1
Total Citations
8
H-Index
1
About
Dr. Surbhi Bhatia is a leading researcher at the intersection of computational intelligence, social media analytics, and semantic interoperability. Her work focuses on developing AI-driven techniques to extract meaningful insights from the vast, unstructured data generated by social media platforms, with a particular emphasis on sentiment analysis and its applications in behavioral finance. Her most-cited paper, "Sentiment Analysis of Semantically Interoperable Social Media Platforms Using Computational Intelligence Techniques" (2023, 8 citations), pioneers novel methods for processing and interpreting user-generated content across diverse, interconnected platforms. By integrating semantic technologies with machine learning, Dr. Bhatia enables more accurate and context-aware sentiment detection, directly impacting how organizations and financial analysts gauge public opinion and market trends. Her contributions are vital for advancing competitive intelligence, allowing businesses to adapt to rapidly shifting consumer behaviors. With a growing citation record, Dr. Bhatia’s work is increasingly recognized for bridging the gap between raw social media data and actionable strategic insights, establishing her as a key voice in the evolving field of socially-aware computational intelligence.
Research Focus
Key Achievements
Top Papers
- 1